Senior Data Scientist

Location: Bengaluru

Company Name :
Willware Technologies
Experience : 10+ Years
Location :
Bangalore
Work Mode :
Onsite
Role :
Senior Data Scientist

Roles and Responsibilities
Important Key words:

- Large Language Models (LLMs)
Classical Machine Learning (Supervised & Unsupervised Learning)
Generative AI
Python
Microsoft Azure
Azure Data Factory & Azure Data Foundry

Your main responsibilities will include
Design, develop, and deploy predictive models including forecasting, classification, regression, and segmentation
Build and customize deep learning NLP models, multimodal models (text + vision), and context‑aware AI solutions.
Implement and tune custom loss functions, advanced quantitative methods, and high‑impact ML algorithms.
Deep knowledge of statistical modeling, experimentation, and advance data analysis.
Conduct rigorous model validation, diagnostics, and performance monitoring.
Perform complex statistical analyses and generate meaningful insights that influence business strategy.
Work closely with product managers, engineering teams, and business leaders to define analytical requirements.
Conduct A/B testing, causal inference, and optimization modeling (linear, mixed‑integer, multi‑objective).
Translate ambiguous business needs into clear analytical frameworks and modeling approaches.
Define and track KPIs and product metrics, supporting data driven prioritization and roadmaps.
Exposure to agentic AI workflows leveraging LLMs, retrieval, tool use, and reasoning systems.

You have the needed skills and qualities to work in analytics, including:
Strong proficiency in Python (Pandas, Num Py, Scikit‑learn; Tensor Flow/PyTorch preferred).
Expertise in SQL, relational databases, data warehouses.
Hands‑on experience with Databricks, large‑scale analytics, and ML workflows.
Deep knowledge of statistical modeling, experimentation, and causal analysis.
Experience working with Azure cloud services.

The following skills are considered distinct advantages:
Work with large‑scale datasets including 1 TB+ data processing for analytics and modeling tasks.
Build, optimize, and maintain data pipelines using Databricks, MLflow, and cloud‑native tooling.
Develop data engineering scripts (e.g., parsers, transformers) required for ML dataset preparation.
Integrate, clean, preprocess, and validate data from multiple sources ensuring governance, accuracy, and compliance